Lead Software Engineer, Data Cloud

Salesforce•Bellevue, WA

About The Position

Salesforce Data 360 is transforming how enterprises unify, analyze, and activate their data at scale. We're seeking a Lead Member of Technical Staff to architect and build the next generation of our control plane services, powering workloads that serve millions of customers worldwide. In this role, you'll lead the evolution of our compute platform, designing systems that orchestrate diverse compute workloads including GPU clusters, batch processing, real-time analytics, and AI/ML systems. You'll work at the intersection of infrastructure, distributed systems, and emerging AI capabilities. You architect and deliver highly scalable, high-quality software while collaborating with geographically distributed engineers and product owners. You bring deep technical expertise and a commitment to engineering excellence, helping define the standards and culture that drive the team forward.

Requirements

10+ years of software engineering experience with deep expertise in distributed systems
Expert-level Kubernetes experience: operators, controllers, scheduling, resource management
Production experience running large-scale infrastructure serving mission-critical workloads
Strong programming skills in Go, Java, Python, or Rust
Deep understanding of containers, orchestration, networking, storage, and compute isolation
Experience designing and building control planes for distributed infrastructure
Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows
Proven technical leadership: driving architecture, mentoring engineers, influencing technical direction

Nice To Haves

Experience with GPU infrastructure and ML/AI workload orchestration
Background in building serverless or function-as-a-service platforms
Expertise in observability tools: Prometheus, Grafana, OpenTelemetry, distributed tracing
Experience with big data processing frameworks (Spark, Flink, Presto, etc.)
Knowledge of vector databases and embedding infrastructure
Contributions to open-source infrastructure projects
Experience in multi-tenant SaaS environments with strong isolation requirements
Familiarity with major cloud providers: AWS, GCP, Azure

Responsibilities

Design and build our next gen Control Plane services
Drive architectural decisions on resource isolation, multi-tenancy, and distributed system design
Evolve compute infrastructure to support diverse workload patterns: batch processing, streaming, interactive queries, and AI/ML workloads at true petabyte scale
Design intelligent job scheduling and orchestration systems to maximize resource utilization
Build platform primitives for capacity management, priority-based allocation, and workload isolation
Implement custom Kubernetes operators and controllers for specialized workload requirements
Develop infrastructure strategies to sustain AI/ML workloads, focusing on GPU management and model deployment
Architect sophisticated resource management protocols optimized for varied and complex compute ecosystems
Partner with infrastructure engineering teams to establish integration frameworks for advancing AI technologies
Lead code reviews, define coding standards, and translate functional requirements into technical requirements — ensuring all developed features meet design and code quality standards while fulfilling customer requirements.
Collaborate with product teams and business partners on product and feature design, coordinating the evaluation, scope, and completion of new development requests.
Assess the impact of new requirements across all upstream and downstream applications, systems, and processes, and work with geographically distributed engineers to ensure successful product delivery.